Staff Data Scientist, Security

Responsibilities

• Provide senior technical direction to data teams on horizontal technical areas, including detection, modeling, metrics, observability, etc. Assume hands-on leadership, especially when helping teams resolve complex problems through iterative execution.
• Identify broad company problems and opportunities that can be tackled through data science. Work with relevant teams to design and build the quantitative outputs and artifacts that deliver outsized value to our users and our business.
• Provide data-driven guidance to cross-functional partners on strategy for tracking and protecting Stripe assets from external and internal threats.
• Contribute to the overall strategy, roadmap, and vision of your data science team and organization.
• Evangelize and inspire best practices across data science. Lead by example to build a culture of craftsmanship and innovation.
• Provide mentorship to our data science talent to help them grow technically and professionally.

Requirements

• 10+ years of data science experience or equivalent combined industry and research experience in a quantitative field.
• Bachelor’s, Master’s, or Ph.D. in a quantitative field (e.g. Statistics, Mathematics, Economics, Operations Research, Quantitative Marketing, Physical Sciences, Engineering, etc.).
• Demonstrated experience of leading organization-wide initiatives spanning multiple teams, or leveraging deep domain expertise to influence tech roadmap planning and execution.
• Demonstrated ability to effectively collaborate across multiple teams and stakeholders to drive business outcomes.
• Experience creating alignment with stakeholders in ambiguous and complex situations, and leading company-level initiatives.
• Demonstrated ability to balance execution and velocity with research, statistical depth, and scalable design.
• Proficiency with AI tools to accelerate model development, analysis, and coding.
• Experience mentoring and investing in the development of peers.

Nice-to-Haves

• Strong preference for experience working with security or security-adjacent teams, and familiarity with contemporary security tools and practices.
• Experience in the end-to-end development and production implementation of machine learning, statistical, or forecasting frameworks (beyond building model prototypes).
• Experience developing and deploying metrics and observability frameworks.